FastFlow is a pattern-based programming framework targeting streaming applications. It implements pipeline, farm, divide and conquer, and their composition, as well as generic streaming networks. It is specifically designed to support the development and the seamless porting of existing applications on multi-core, GPGPUs, and clusters of them. The layered template-based C++ design ensures flexibility and extendibility. Its lock-free/fence-free run-time support minimizes cache invalidation traffic and enforces the development of high-performance (high-throughput, low-latency) scalable applications. It has been proven comparable or faster than TBB, OpenMP, and Cilk on several micro-benchmarcks and real-world applications, especially when dealing with fine-grained parallelism and high-throughput applications.

Charm++ is a portable adaptive runtime system for parallel applications. Application developers create an object-based decomposition of the problem of interest, and the runtime system manages issues of communication, mapping, load balancing, fault tolerance, and more. Sequential code implementing the methods of these parallel objects is written in C++. Calls to libraries in C++, C, and Fortran are common and straightforward. Charm++ is portable across individual workstations, clusters, accelerators (Cell SPEs and GPUs), and supercomputers such as those sold by IBM (Blue Gene, POWER) and Cray (XT3/4/5/6). Applications based on Charm++ are used on at least 5 of the 20 most powerful computers in the world.

POP-C++ is a comprehensive object-oriented system for developing applications in large distributed computing infrastructures such as Grid, P2P or Clouds. It consists of a programming suite (language, compiler) and a run-time system for running POP-C++ applications. The POP-C++ language is a minimal extension of C++ that implements the parallel object model with the integration of resource requirements into distributed objects. This extension is as close as possible to standard C++ so that programmers can easily learn POP-C++ and so that existing C++ libraries can be parallelized using POP-C++ without too much effort. The POP-C++ run-time is an object-oriented open design that aims at integrating different distributed computing tool kits into an infrastructure for executing requirement-driven object-oriented applications. It uses objects to serve objects: the system provides services for executing remote objects.

Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.

Son of Grid Engine is a highly-scalable and versatile distributed resource manager for scheduling batch or interactive jobs on clusters or desktop farms. It is a community project to continue Sun's Grid Engine. It is competitive against proprietary systems and provides better scheduling features and scalability than other free DRMs like Torque, SLURM, Condor, and Lava.

YML is a research project that aims to provide tools for using global computing middleware such as GRID, peer to peer, and metacomputing environments. The YML software architecture enables the definition of parallel applications, independently of the underlying middleware used. Parallel applications are defined using a workflow language called YvetteML.

HPCC (High Performance Computing Cluster) stores and processes large quantities of data, processing billions of records per second using massive parallel processing technology. Large amounts of data across disparate data sources can be accessed, analyzed, and manipulated in fractions of seconds. HPCC functions as both a processing and a distributed data storage environment capable of analyzing terabytes of information.

ScalaBLAST is a high-performance multiprocessor implementation of the NCBI BLAST library. It supports all 5 primary program types (blastn, blastp, tblastn, tblastx, and blastx) and several output formats (pairwise, tabular, and XML). It will run on most multiprocessor systems which have MPI installed, and can run over a wide variety of interconnects, including infiniband, quadrics, and ethernet. It is designed to run a large number of queries against either large or small databases. It parallelizes the BLAST calculations by dynamically scheduling them across processors using a fault-resilient scheme.